导入依赖包
import numpy as np
import matplotlib.pyplot as plt
import sklearn.preprocessing as sp
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False正态分布化
y = np.random.randint(1, 101, 200)
ys = sp.scale(y)
(y.mean(axis=0), y.std(axis=0), ys.mean(axis=0), ys.std(axis=0))
# (48.755, 29.599577277386917, -1.0658141036401502e-16, 1.0)